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Dynamic 3D UAV Placement Optimization: Improved Bonobo Optimizer for Enhanced Coverage and Communication 35

Dynamic 3D UAV Placement Optimization: Improved Bonobo Optim...

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35th ieee International symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Yahia, Selma Taleb, Sylia Mekhmoukh Loscri, Valeria Saadi, Amylia Ait Ho, Tu Dac Vo, Van Nhan Eldeeb, Hossien Muhaidat, Sami Inria Lille-Nord Europe Lille 59000 France University of m'Hamed Bougara List Laboratory Boumerdes35000 Algeria Esme Engineering School Ivry-sur-Seine94200 France Norwegian University of Science and Technology Department of Information Security and Communication Technology Norway The Arctic University of Norway Department of Electrical Engineering Norway Duy Tan University Faculty of Information Technology Viet Nam Duy Tan University The Institute of Research and Development Viet Nam Khalifa University 6G Research Center Computer and Communication Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350362244

Unmanned aerial vehicles (UAVs) offer a promising solution for enhancing network coverage, reliability, and data speed in future wireless network generations. However, deploying UAVs as aerial base stations requires careful consideration of crucial design factors, including three-dimensional (3D) placement and performance optimization tailored to specific applications. In this paper, the 3D placement of multiple UAVs, acting as aerial base stations, is investigated in a dynamic user scenario. First, a closed-form expression for the coverage probability is derived. Then, to maximize the network coverage and sum rate while ensuring reliable and energy efficient system, a joint multi-objective optimization problem is formulated considering the real-time user movements. To solve the problem, an improved Chaos-based Bonobo Optimizer (CBO) scheme is proposed which combines chaotic maps with the Bonobo Optimizer (BO) algorithm. The obtained results demonstrate the superior performance of the proposed approach compared with different benchmark algorithms. The results reveal that the proposed CBO algorithm offers a minimum of 1 5 % and 9 0 ~ M b i t / s ~ i m p r o v e m e n t s ~ in coverage and sum rate, respectively. © 2024 ieee.

关键词： Unmanned aerial vehicles (UAV)

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Design and Implementation of Weather Monitoring and Prediction System 3rd

Design and Implementation of Weather Monitoring and Predicti...

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3rd International Conference on Advanced Computing and applications, ICACA 2024

作者： Sikdar, Sougata Karmakar, Koushik Biswas, Suparna Bengal College of Engineering and Technology Durgapur India Narula Institute of Technology Kolkata India Maulana Abul Kalam Azad University of Technology Kolkata India

ISBN: (纸本)9789819747986

For the last few years, a lot of research works are carried out on different intelligent technologies like Internet of Things (IoT) and machine learning. Their implementation is possible through a variety of IoT hardware platforms like ESP8266 chip. In the paper we have proposed a method for automatically weather monitoring system that has access to the dynamic as well as real-time atmospheric data within a specific range. IoT, embedded systems, along with the machine learning concepts provide foundation of this weather monitor system. Additionally, the system uses wireless technologies like sensors and other electrical gadgets. Primary objective of the proposed system is to use sensors for sensing different atmospheric conditions like temperature, humidity, rainfall and air pressure. Data has been collected through the sensors and uploaded to ThingSpeak server. This information is also displaced on a webpage from where users may view them. Machine learning environment is built up using different methods like the Logistic Regression model, KNN, SVM, Gaussian naivebayes, XGBoost and ANN. These models are trained based on previous records that are available from different sensors. Additionally, NodeMCU collects sensor data, including temperature, humidity, rainfall and pressure and is uploaded to a ThingSpeak cloud server. These data are then stored in a comma separated Value (CSV) file. Later it is transferred to a Jupyter notebook which runs on Python environment. In this experiment only, real-time data collected from different sensors has been used. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rain

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Resource-efficient VLSI Architecture of Softmax Activation Function for real-time Inference in Deep Learning applications

Resource-efficient VLSI Architecture of Softmax Activation F...

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2023 International symposium on Devices, Circuits and Systems, ISDCS 2023

作者： Ther, Akash Kumar Pandit, Binit Ganguly, Anirban Chakraborty, Anirban Banerjee, Ayan Electronics and Telecommunication Engineering Iiest Shibpur W.B. Howrah India Electrical and Electronics Engineering Biet Hyderabad T.S Hyderabad India Computer Science and Technology Uem Kolkata W.B Kolkata India

ISBN: (纸本)9798350315042

The Softmax activation function layer is the output layer in various Deep Learning (DL) models for multi-class classification applications. It computes the probability values for each input entry to the layer and represents the degree of confidence. The nonlinearity of the softmax function poses a challenge of increased hardware complexity. Therefore, the proposed VLSI architecture of the softmax activation function aims to reduce hardware resources with minimal loss in accuracy. The proposed architecture utilizes an optimized design of a ROM-based exponential unit for exponentiation and a Newton-Raphson iterations-based division by reciprocation unit for division operation. The proposed architecture is evaluated on Xilinx's Kirtex-7 KC705 FPGA Evaluation Platform, achieving LUTs 1.44 - 11.61 × lesser than the other state-of-the-art architectures on the MNIST dataset. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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Tracking a Hand in real time with Accelerometers for VR applications

Tracking a Hand in Real Time with Accelerometers for VR Appl...

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Opportunity Research Scholars symposium (ORSS)

作者： Baylor McElroy Alex Diviney Steve C. Chiu Ahmed F. Ashour Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA

ISBN: (数字)9798350390698

ISBN: (纸本)9798350390704

Virtual reality (VR) technology presents a paradigm shift in human-computer interaction, offering unprecedented mobility, immersion, and customization. However, current input devices for VR applications lack the portability, speed, and computational feasibility required for mainstream adoption. This paper proposes a novel solution using wearable sensors and an embedded processor to address these challenges. Specifically, we explore the feasibility of tracking hand movements in real-time using five accelerometers mounted on the fingers, coupled with a cost-effective processor. Our methodology involves signal smoothing, hand and finger vector separation, and tracking one-dimensional tapping gestures. Experimental results demonstrate the effectiveness of a moving average filter in reducing signal noise, and the challenges in accurately isolating finger motion vectors. Despite remaining challenges, such as gravity-induced acceleration deflection, our findings underscore the potential of our approach in enabling intuitive and responsive hand tracking for VR interactions. This research lays the groundwork for developing improved input devices tailored to the unique requirements of VR environments, contributing to the advancement and widespread adoption of VR technology.

关键词： Accelerometers Smoothing methods Tracking Noise Input devices Virtual reality Vectors real-time systems Usability Wearable sensors

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Optimized memcpy for 32-bit ARM Automotive embedded Systems

Optimized memcpy for 32-bit ARM Automotive Embedded Systems

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TRON symposium (TRONSHOW)

作者： Yucan Yu Yongsheng Daniel Zhou Ying Taat Soh Muhamed Fauzi Bin Abbas Infocomm Technology Singapore Institute of Technology Singapore Singapore Software and Central Technologies Continental Automotive Singapore Singapore

ISBN: (数字)9784893624123

ISBN: (纸本)9798331540302

Efficient memory operations are critical for real-time performance in automotive embedded systems. The memcpy function, widely used in communication and graphical processing tasks, often falls short of meeting the low latency requirements when using the standard C *** paper introduces an optimized memcpy algorithm for 32-bit ARM microcontrollers, leveraging assembly-level enhancements to maximize microcontroller register usage and integrate advanced techniques such as byte-shifting and cache prefetching. Context-aware optimizations tailored for automotive applications improve aligned and unaligned data transfers across various memory types, achieving up to an eightfold increase in *** results highlight significant performance improvements, especially in unaligned memory access scenarios, positioning the optimized memcpy as a robust and efficient solution for automotive embedded systems.

关键词： embedded systems Microcontrollers Prefetching Memory management Automotive applications Data transfer Throughput real-time systems Registers Optimization

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A High-Performance ORB Accelerator with Algorithm and Hardware Co-design for Visual Localization

A High-Performance ORB Accelerator with Algorithm and Hardwa...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： Xiuyuan Qi Ye Liu Shuang Hao Zherong Liu Kun Huang Minghui Yang Liang Zhou Jun Zhou University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Vision-based localization plays an important role in numerous emerging applications, including mobile robots, UAVs, AR/VR, etc. The ORB algorithm is a very classic algorithm in visual localization, typically consisting of feature point extraction and matching. Owing to the extensive computational load involved in these processes, real-time performance remains difficult in applications based on embedded devices. In this work, we present a high-performance ORB accelerator through the algorithm and hardware co-design, including a three-levels parallel processing architecture to improve performance, a pixel-level RS-BRIEF descriptor generator to reduce the computational complexity, and an on-chip sliding storage bucket matching and overwriting strategy for storage optimization. The proposed work has been implemented on the ZCU104 FPGA board achieving a high-performance (108 FPS) and a low average trajectory error at the cost of slightly fewer hardware resources compared with some SOTA works.

关键词： Location awareness Performance evaluation Visualization Parallel processing Feature extraction Hardware real-time systems

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real-time Scheduling Algorithm for Mixed-Criticality Systems on Multi-Core Processor Platforms 8

Real-Time Scheduling Algorithm for Mixed-Criticality Systems...

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8th International symposium on System Security, Safety, and Reliability, ISSSR 2022

作者： Li, Meng Hu, Bitao Xiao, Kun Yang, Ningkang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781665453974

ISBN: (纸本)9781665453974

It is becoming a trend for embedded systems to integrate tasks with different critical levels that were originally deployed in several independent processors into one hardware platforms with multi-core processor. This requires that the operating system can correctly schedule tasks with different critical levels on the multi-core processor, but the traditional real-time operating system can't meet this requirement well. In this paper, we design and implement a real-time scheduler for mixed-criticality systems, which can be used in the microkernel operating system for multi-core processor platforms. In our system, time sensitivity and critical level are decoupled based on task partition policy, time slice misappropriation and temporal isolation mechanism. We also carried out testing and analysis work on the evaluation board for Allwinner T3, and experimental results proves that the function of our scheduling algorithm is correct and the performance is good. © 2022 ieee.

关键词： embedded systems

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Investigating Effective Spectral Bands for Tissue Visualization in Oral Mucosa

Investigating Effective Spectral Bands for Tissue Visualizat...

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2023 ieee International symposium on Medical Measurements and applications, MeMeA 2023

作者： Chand, Sneha Raj, Antony Preejith, Sp Sivaprakasam, Mohanasankar Indian Institute of Technology Madras Department of Electrical Engineering Chennai India Indian Institute of Technology Madras Healthcare Technology Innovation Centre Chennai India

ISBN: (纸本)9781665493840

Detection of malignancies in the gastrointestinal tract through endoscopic investigations is crucial for managing the disease and improving cancer prognosis. However, current standard endoscopic procedures using white light sources have limitations in providing comprehensive tissue information. To address this issue, spectral imaging technology has been developed, which allows light to penetrate different tissue layers to capture the true spectral response of a tissue. The study discussed here focuses on using spectral imaging to image the sublingual region of the oral mucosa using a broadband light source and five different individual light illuminations to understand the characteristics of vascular structures under different wavelengths. This approach has the potential to provide valuable insights into the structure and function of different tissues and could lead to improvements in the detection and diagnosis of a wide range of diseases, including oral cancer. This study focuses on imaging the sublingual region of the oral mucosa using the broadband light source and five different individual light illuminations to understand the characteristics of vascular structures under different wavelengths. The study using Weber's contrast, reveals that superficial blood vessels (SBV) have high contrast values at low wavelengths, while deep-seated blood vessels (DSBV) have high contrast values at higher wavelengths. This study confirms the findings of our previous study in a different system. The paper emphasizes the importance of using spectral imaging to capture comprehensive tissue information for the early detection of cancer and improved prognosis. The study highlights the need for an appropriate light source and the usage of individual LEDs for building a standalone system to effectively visualize vascular features. Further research on a larger scale is necessary to translate these findings into practical use for real-time endoscopic investigations. © 2023 ieee.

关键词： Tissue

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Cycle-Accurate FPGA Emulation of RRAM Crossbar Array: Efficient Device and Variability Modeling with Energy Consumption Assessment 25

Cycle-Accurate FPGA Emulation of RRAM Crossbar Array: Effici...

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25th ieee Latin American Test symposium, LATS 2024

作者： Wen, Jianan Vargas, Fabian Luis Zhu, Fukun Reiser, Daniel Baroni, Andrea Fritscher, Markus Perez, Eduardo Reichenbach, Marc Wenger, Christian Krstic, Milos University Of Rostock Rostock Germany Germany Brandenburg University Of Technology Cottbus-Senftenberg Cottbus Germany University Of Potsdam Potsdam Germany

ISBN: (纸本)9798350365559

Emerging device technologies such as resistive RAM (RRAM) are increasingly recognized in enhancing system performance, particularly in applications demanding extensive vector-matrix multiplications (VMMs) with high parallelism. However, a significant limitation in current electronics design automation (EDA) tools is their lack of support for rapid prototyping, design space exploration, and the integration of inherent process-dependent device variability into system-level simulations, which is essential for assessing system reliability. To address this gap, we introduce a field-programmable gate array (FPGA) based emulation approach for RRAM crossbars featuring cycle-accurate emulations in real time without relying on complex device models. Our approach is based on pre-generated look-up tables (LUTs) to accurately represent the RRAM device behavior. To efficiently model the device variability at the system level, we propose using the multivariate kernel density estimation (KDE) method to augment the measured RRAM data. The proposed emulator allows precise latency determination for matrix mapping and computation operations. Meanwhile, by coupling with the NeuroSim framework, the corresponding energy consumption can be estimated. In addition to facilitating a range of in-depth system assessments, experimental results suggest a remarkable reduction of emulation time compared to the classic behavioral simulation. © 2024 ieee.

关键词： Reliability

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YOLOv9-Enabled Vehicle Detection for Urban Security and Forensics applications 12

YOLOv9-Enabled Vehicle Detection for Urban Security and Fore...

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12th International symposium on Digital Forensics and Security, ISDFS 2024

作者： Bakirci, Murat Bayraktar, Irem Tarsus University Unmanned/Intelligent Systems Lab Faculty of Aeronautics and Astronautics Mersin Turkey

ISBN: (纸本)9798350330366

The integration of artificial intelligence (AI) techniques in vehicle detection holds significant promise, particularly in forensic and security domains. Leveraging object detection algorithms enables real-time monitoring of vehicles by competent authorities, aiding in continuous surveillance of roads and highways for various surveillance objectives. Additionally, it streamlines tasks such as identifying stolen vehicles, tracking suspects, and enforcing traffic regulations. Object detection technology also proves invaluable in forensic analysis, aiding criminal investigations and accident reconstructions. Furthermore, it enhances security by detecting aberrant behavior and potential threats at critical infrastructure sites. Concurrently, the remarkable advancements in unmanned aerial vehicles (UAVs) have led to their widespread application across diverse domains, including traffic monitoring and intelligent transportation systems. Equipped with high-resolution cameras, UAVs offer precise imagery for vehicle detection, facilitating swift responses to incidents. This study focuses on vehicle detection from aerial urban transportation images using YOLOv9 on a UAV platform, demonstrating the feasibility and efficacy of aerial analysis for efficient vehicle detection and timely alerts to competent authorities. © 2024 ieee.

关键词： Antennas

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